Many-objective bi-level energy scheduling method for integrated energy stations based on power allocation strategy

Area of Science:

• Energy Systems Engineering
• Renewable Energy Integration
• Optimization Theory

Background:

• Integrated energy stations are crucial for new energy vehicle infrastructure.
• Efficient utilization of renewable energy sources like wind and photovoltaics (PV) remains a challenge.
• Existing models may not fully optimize the complex interplay of energy generation, storage, and consumption.

Purpose of the Study:

• To propose an integrated energy station (WPIES) combining hydrogen, charging, and power exchange functionalities.
• To develop a future value competition strategy (FVCS) for optimizing wind and PV allocation within the WPIES.
• To enhance overall energy utilization efficiency and economic benefits of the integrated energy station.

Main Methods:

• A two-layer optimization model integrating FVCS and WPIES was developed.
• The upper layer maximizes expected income.
• The lower layer optimizes profit, minimizes battery losses, and reduces pollutant emissions, considering hydrogen power constraints.

Main Results:

• The proposed FVCS-WPIES model demonstrates superior performance compared to traditional approaches.
• The optimization model effectively balances competing objectives, including economic gains and environmental impact.
• Pareto solutions derived from the model offer significant improvements in overall system efficiency.

Conclusions:

• The FVCS-WPIES model provides an effective framework for managing integrated energy stations.
• Optimized allocation of wind and PV power significantly improves energy utilization efficiency.
• The proposed strategy offers a promising solution for enhancing the economic and environmental performance of renewable energy systems.